Cross-library API recommendation using web search engines

Abstract

Software systems are often built upon third party libraries. Developers may replace an old library with a new library, for the consideration of functionality, performance, security, and so on. It is tedious to learn the often complex APIs in the new library from the scratch. Instead, developers may identify the suitable APIs in the old library, and then find counterparts of these APIs in the new library. However, there is typically no such cross-references for APIs in different libraries. Previous work on automatic API recommendation often recommends related APIs in the same library. In this paper, we propose to mine search results of Web search engines to recommend related APIs of different libraries. In particular, we use Web search engines to collect relevant Web search results of a given API in the old library, and then recommend API candidates in the new library that are frequently appeared in the Web search results. Preliminary results of generating related C# APIs for the APIs in JDK show the feasibility of our approach.